Extended state observer-based adaptive sliding mode control of differential-driving mobile robot with uncertainties

Cui, Mingyue; Liu, Wei; Liu, Hongzhao; Jiang, Hualong; Wang, Zhipeng

doi:10.1007/s11071-015-2355-z

Cited by 89 publications

(68 citation statements)

References 26 publications

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“…Hence, a strategy to obtain the upper bound of the system perturbation or a method that does not require this knowledge is needed. The adaptation SMC approach proposed in [9] offers an effective tool to solve this problem. Please refer to [39] for more discussion about adaptive SMCs as they are out of the scope of the current study. Remark 6 It is clear that the convergence speed of the system states is determined by

β

.…”

Section: Resultsmentioning

confidence: 99%

“…It is well known that SMC is totally invariant with respect to a subset of uncertainties satisfying the so‐called matching condition, that is, perturbations that enter the state equation at the same point as the control input. Numerous SMC methods have been proposed for the systems with matched uncertainties, such as stabilisation by SMC [4], sliding mode tracking control [5], optimal SMC [6], sliding mode regulation [7], adaptive SMC [8], observer based SMC [9] and so on. However, these methods considered only the matched uncertainties.…”

Section: Introductionmentioning

confidence: 99%

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Robust integral sliding mode‐ control of one‐sided Lipschitz non‐linear systems

Saad

Sellami

García

2018

IET Control Theory & Applications

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β

.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust integral sliding mode‐ control of one‐sided Lipschitz non‐linear systems

Saad

Sellami

García

2018

IET Control Theory & Applications

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“…In order to upgrade the tracking control performance of the AGR, the nonlinear dynamic techniques are adopted for linearization [12], sliding mode control [13], or smart decision [14]. Recently, an improved linear extended state observer with error compensating term has been mentioned [15]. In reality, the uncertain nonlinear kinematic model still exists.…”

Section: Literature Reviewmentioning

confidence: 99%

High Performance of an Adaptive Sliding Mode Controller under Varying Loads for Lifting-Type Autonomous Grounded Robot

et al. 2020

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To work in shared space with humans, autonomous systems must carry unknown loads in predefined missions. With the conventional control scheme, the grounded robot would suffer unstable motion and imprecise tracking performance. To overcome these challenges, in this paper, a novel controller using an adaptive sliding mode for autonomous grounded robots (AGR) is proposed. This control strategy takes into consideration uncertain characteristics, varying loads, and external disturbances. To analyze the tracking performance precisely, the overall error of motion system is decoupled into two subsystems where the second-order system is related to the angular tracking error and the third-order system is associated with the linear one. Initially, the dynamics model of the grounded robot is established containing different elements of nonlinear forces in order to address the technical problems. Then, the system state equation of the autonomous system is mentioned to indicate the theoretical characteristics. Based on the proposed controller, the stability of the system is validated by the Lyapunov theorem. From the results of numerical tests, three practical situations consisting of separately linear and circular trajectories with varying loads and an S-curve trajectory of a working map are suggested. The tracking performance validates that the proposed control scheme is, in various scenarios, robust, effective, and feasible. From these superior outcomes, it can be determined obviously the property of our works in accommodating the variations of cargo from applications in distribution centers, material transportation, or handling equipment.

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“…e robustness and the efficiency of this control system were proven by the simulation results. Furthermore, a sliding mode controller was developed in [6] to achieve a trajectory tracking of mobile robots with parametric variations and external disturbances. e asymptotic convergence of tracking errors was shown using Lyapunov's theory.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Observer-Based Output Feedback Control for Two-Wheeled Self-Balancing Robot

Jmel

Dimassi

Said

et al. 2020

Mathematical Problems in Engineering

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In this paper, an output feedback control approach based on an adaptive observer is developed for the two-wheeled self-balancing robot subject to unknown parameters (with nonlinear parameterization). Firstly, a high gain control method with state feedback is proposed. Then, an adaptive observer is designed to estimate the unknown state and the unknown body mass of the robot which influences the height of the center of mass. Next, the adaptive observer is combined with the designed high gain controller: a Lyapunov-based stability analysis of the closed loop system is developed to establish the convergence of the tracking error as well as estimation and adaptation errors. Simulation results assert the performance of the developed tracking control scheme for the two-wheeled self-balancing robot subject to mass variation.

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Extended state observer-based adaptive sliding mode control of differential-driving mobile robot with uncertainties

Cited by 89 publications

References 26 publications

Robust integral sliding mode‐ control of one‐sided Lipschitz non‐linear systems

Robust integral sliding mode‐ control of one‐sided Lipschitz non‐linear systems

High Performance of an Adaptive Sliding Mode Controller under Varying Loads for Lifting-Type Autonomous Grounded Robot

Adaptive Observer-Based Output Feedback Control for Two-Wheeled Self-Balancing Robot

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